This invention relates to the field of
business process risk management technology, specifically to an
artificial intelligence-based
business process risk
management system and method. It includes a node segmentation module, a region segmentation module, a
model building module, a threshold optimization module, and a
risk assessment module. The node segmentation module acquires process data from all of an enterprise's business operations, segments the process data into process nodes, and extracts the risk materials, normal materials, and applicants corresponding to each process node. Through a multi-module collaborative closed-
loop design, it effectively solves many shortcomings of existing technologies. Firstly, it significantly improves the accuracy of
risk identification. Secondly, by adapting node-specific semantic models and combining the review attributes of process nodes to extract semantic features in a customized manner, it avoids the semantic generalization problem of general models.